Statistical Design and Analysis for Intercropping Experiments (Two Crops) - Springer Series in Statistics Softcover Reprint of the Original 1st Ed. 1993 edition

Description for Sales People: This textbook provides a comprehensive survey of design and analysis of experiments for intercropping experiments. Its main themes are that techniques such as relative indices make it possible to cover a wide variety of conditions, and that statistical models for density-yield relations enable recommendations to be made to growers of crops. Table of Contents: 1 Introduction and Definitions.- 1.1. Introduction and Objectives.- 1.2. Statistical Design.- 1.3. Types of Treatment.- 1.4. Treatment Designs in Category 4 for Intercropping Experiments.- 1.5. Some Statistical Problems Associated with Response Model Equations, Statistical Analyses, and Inferences.- 1.6. Some Concepts and Definitions.- 1.7. Literature Cited.- 2 One Main Crop Grown with a Supplementary Crop.- 2.1. Objectives and Introduction.- 2.2. Some Examples of Main Crops Grown with a Supplemental Crop.- 2.3. Statistical Designs and Univariate Analyses of Main Crop Yields for Experiments on Main and Supplemental Crops.- 2.4. Some Additional Statistical Analyses for Yields of Main Crop Intercropped with a Supplemental Crop.- 2.5. Multivariate Analyses for a Main Crop Grown with Supplemental Crops and Grown as a Sole Crop.- 2.6. Summary and Discussion.- 2.7. Problems.- 2.8. Literature Cited.- 3 Both Crops Main Crops Density Constant Analyses for Each Crop Separately.- 3.1. Objectives and Introduction.- 3.2. Treatment and Experiment Designs.- 3.3. Univariate Analyses on Observed Variables for Each of the Two Main Crops.- 3.4. Multivariate Analyses on a Vector of Observed Variables of One Crop.- 3.5. Summary and Discussion.- 3.6. Problems.- 3.7. Literature Cited.- 4 Both Crops Main Crops Density Constant Combined Crop Responses.- 4.1. Objectives and Introduction.- 4.2. Univariate Analyses on Functions of Combined Variables of Both Crops.- 4.3. Land Equivalent Ratio or Relative Yield Total.- 4.4. Multivariate Analysis on an Observation Vector of the Intercropping Systems.- 4.5. Effect of Varying Proportions on Created Functions.- 4.6. Summary and Discussion.- 4.7. Problems.- 4.8. Literature Cited.- Appendix 4.1.- 5 Both Crops of Major Interest with Varying Densities.- 5.1. Objectives and Introduction.- 5.2. Treatment Design and Statistical Analysis for Comparisons Among Density Combinations for Individual Crop Responses.- 5.3. Statistical Analyses for Responses from Both Crops for a Single Pair of Crops at Varying Densities.- 5.4. Models and Analyses for Monocultures and Mixtures of Two Crops over a Range of Densities.- 5.5. Analyses for c1 Lines of Crop 1 and c2 Lines of Crop 2.- 5.6. Summary and Discussion.- 5.7. Problems.- 5.8. Literature Cited.- Appendix 5.1. Derivation of Parameter Estimates and Their Variances Using a Generalized Least Squares Method for the Linear Model of Section 5.4 (Prepared by Anila Wijesinha).- Appendix 5.2. Distribution of Estimators and Hypothesis Tests (Prepared by Anila Wijesinha).- 6 Monocultures and Their Pairwise Combinations when Responses Are Available for Each Member of the Combination.- 6.1. Introduction.- 6.2. Treatment Design.- 6.3. A Response Model and Some Statistical Analyses.- 6.4. Summary and Discussion.- 6.5. Problems.- 6.6. Literature Cited.- Appendix 6.1.- Appendix 6.2.- 7 Monocultures and Their Pairwise Combinations when Separate Crop Responses Are Not Available.- 7.1. Introduction.- 7.2. Treatment Designs.- 7.3. Response Model Equations and Some Statistical Analyses.- 7.4. Response Models for a Crop Competition Experiment.- 7.5. Summary and Discussion.- 7.6. Problems.- 7.7. Literature Cited.- Appendix 7.1. Derivation of Solutions for Response Model for Design 3.- Appendix 7.2. Derivation of Solutions and Variances for Model 4, Example 7.5.- 8 Spatial and Density Arrangements.- 8.1. Introduction.- 8.2. Spatial Arrangements Density Constant.- 8.3. Spatial Arrangements Density Variable.- 8.4. Statistical Analyses for the Arrangements in Section 8.3.- 8.5. Summary and Discussion.- 8.6. Problems.- 8.7. Literature Cited.- 9 Some Analytical Variations for Intercropping Studies.- 9.1. Introduction.- 9.2. Replacement Series.- 9.3. Other Indices.- 9.4. Linear Programming.- 9.5. Summary and Discussion.- 9.6. Problems.- 9.7. Literature Cited.- 10 Experiment Designs for Intercropping Experiments.- 10.1. Introduction.- 10.2. Principles of Design of Experiments.- 10.3. Zero-Way Elimination of Heterogeneity.- 10.4. One-Way Elimination of Heterogeneity.- 10.5. Two-Way Elimination of Heterogeneity.- 10.6. Split Plot and Split Block Designs.- 10.7. More Complex Experiment Designs.- 10.8. Plot Technique.- 10.9. Stability Concepts and Parsimonious Experiment Design.- 10.10. Problems.- 10.11. Literature Cited."

Contributor Bio:  Federer, Walter T WALTER T. FEDERER, PHD, is Liberty Hyde Bailey Professor of Biological Statistics, Emeritus, at Cornell University. He has held numerous posts as editor, secretary, and president of various journals and societies, and he is also a Fellow or member of more than a dozen local, regional, national, and international associations. Dr. Federer received the Honor Alumnus Achievement Award and Honored Alumnus Award from Colorado State University and the Distinguished Service in Agriculture Award from Kansas State University. FREEDOM KING, PHD, is Teaching Support Specialist in the Department of Biological Statistics and Computational Biology at Cornell University. His areas of interest include generalized linear mixed models, experimental designs, categoricaldata analysis, and statistical computing with an emphasis on work sales through SAS(R) programming techniques.